The atomic simulation environment (ASE) is a software package written in the Python
programming language with the aim of setting up, steering, and analyzing atomistic …

Genetic algorithms are on the rise in electromagnetics as design tools and problem solvers
because of their versatility and ability to optimize in complex multimodal search spaces. This …

首先阐述遗传算法的原理和求解问题的一般过程; 然后讨论了近年来从遗传算子,
控制参数等方面对遗传算法的改进, 并对遗传算法在计算机科学与人工智能 …

Machine learning is widely used to develop classifiers for security tasks. However, the
robustness of these methods against motivated adversaries is uncertain. In this work, we …

The authors showcase the potential of symbolic regression as an analytic method for use in
materials research. First, the authors briefly describe the current state-of-the-art method …

For centuries, scientists have attempted to identify and document analytical laws that
underlie physical phenomena in nature. Despite the prevalence of computing power, the …

Rainfall-Runoff Modelling: The Primer, Second Edition is the follow-up of this popular and
authoritative text, first published in 2001. The book provides both a primer for the novice and …

Nanoscale inorganic wheel-shaped structures are one of the most striking types of
molecular aggregations. Here, we report the synthesis of a gigantic lanthanide wheel cluster …

Social insects--ants, bees, termites, and wasps--can be viewed as powerful problem-solving
systems with sophisticated collective intelligence. Composed of simple interacting agents …

The generalized Born (GB) model is one of the fastest implicit solvent models, and it has
become widely adopted for Molecular Dynamics (MD) simulations. This speed comes with …